M.Tech. (Computational and Data Science)
Get all the information you need about the M.Tech. (Computational and Data Science) course structure, duration, core courses, soft core courses, dissertation, and electives.
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Universal Two-Qubit Computational Register for Trapped Ion Quantum Processors
Universal two-qubit computational register for trapped ion quantum processors, including state preparation, gates, and benchmarking. The experimental setup and results are discussed.
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Computational Physics (Lecture 18)
The basic structure of MPICH and its features in Computational Physics Lecture 18. Understand how MPI functions are used and linked with a static library provided by the software package. Explore how P4 offers functionality and supports parallel computer systems. Discover the concept of clusters in
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Cryptographic Reductions and Learning in Computational Complexity
This lecture explores the connection between computational complexity and cryptography, focusing on topics like pseudorandom functions, public-key cryptography, and learning from Gaussians. It delves into the implications of cryptographic reductions, lower bounds for learning MLPs, and the existence
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Understanding Signed Integers and Addition in Computational Systems
Dive into the world of signed integers, extensions, truncations, and addition in computer science with a focus on how negative values are represented and operated on. Explore concepts like sign-magnitude and two's complement representations, uncovering the intricacies of handling integers in computa
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OBPMark and OBPMark-ML: Computational Benchmarks for Space Applications
OBPMark and OBPMark-ML are computational benchmarks developed by ESA and BSC/UPC for on-board data processing and machine learning in space applications. These benchmarks aim to standardize performance comparison across different processing devices, identify key parameters, and provide recommendatio
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Computational thinking as 21st Century skill
Computational thinking is a critical skill for the digital age, involving problem-solving techniques that enable computers to process information effectively. It precedes programming and requires breaking down complex problems into manageable steps. Educators emphasize computational thinking exercis
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Computational Geometry.
Voronoi diagrams, a key concept in computational geometry, involve partitioning a space based on points sites. They have diverse applications like nearest neighbor queries and facility location. The diagrams consist of Voronoi cells, edges, and vertices, forming a connected graph. Properties include
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Master's Program in Computational Drug Discovery and Development - Fall 2024 Curriculum
This Master's program offers a comprehensive curriculum focusing on Artificial Intelligence, Computational Drug Discovery, and Development. With a blend of cutting-edge technologies and practical applications, students delve into techniques, AI/ML, big data mining, modeling, and more. Through intens
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Understanding Computational Linguistics and Natural Language Processing
Explore the fascinating fields of Computational Linguistics and Natural Language Processing (NLP), delving into their development, applications, and significance. Learn about the study of human languages in computational models, the importance of corpora in linguistic research, and the various types
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Understanding the Importance of Pattern Recognition in Computational Thinking
Pattern recognition is a vital skill in computational thinking, enabling the identification of similarities and differences between concepts and objects. By recognizing patterns, individuals can efficiently solve complex problems, create shortcuts, and avoid duplications in problem-solving processes
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Engaging Paper-Based Problem Solving for Computational Thinking Skills
Implementing paper-based problem-solving activities using puzzles, riddles, and pattern recognition can effectively introduce computational thinking without the need for complex technology or terminology. Through real-life scenarios like transporting a fox, chicken, and corn across a river or encodi
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Insights on Computational Complexity Threshold Results
Exploring the challenges in proving major lower bounds for computational complexity, focusing on the Hardness Magnification and Minimum Circuit Size Problem (MCSP). Discusses the difficulties in proving weak and strong LBs, highlighting recent theorems and barriers that impact progress in the field.
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Recent Advances in Computational Doppler Radar Data Modeling
Explore the latest developments in computational modeling of Doppler radar data, focusing on error estimation, dual vs. single pol radars comparison, uncertainty quantification, and methodology for analyzing Doppler radar predictions against gauge measurements. The study involves data from multiple
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Understanding High Dynamic Range Sensors in Computational Photography
Dive into the world of High Dynamic Range (HDR) sensors in computational photography with topics covering sensor architectures, CMOS sensing techniques, dynamic range evaluation, and basic concepts related to image sensors and pixel integrators. Explore the importance of dynamic range in capturing a
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Computational Photography: Texture Synthesis and Hole-Filling Overview
Delve into the world of texture synthesis and hole-filling in computational photography, exploring the challenges, goals, and techniques involved in creating new textures and filling in image gaps. Learn about building probability distributions, modeling textures, and the intricacies of synthesizing
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Image-Based Lighting in Computational Photography
Explore the techniques and concepts of image-based lighting in computational photography through slides covering topics such as rendering objects in images, using environment maps and light probes, mirrored spheres, and dealing with light sources like the sun. Learn about capturing and utilizing lig
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Computational Thinking, Algorithms & Programming Overview
This unit covers key concepts in computational thinking, including decomposition, abstraction, and algorithmic thinking. Decomposition involves breaking down complex problems, abstraction focuses on identifying essential elements, and algorithmic thinking is about defining clear instructions to solv
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Introducing MatFlow: Open-source Python Tool for Computational Materials Science
MatFlow is an open-source Python code designed for computational materials science, running on HPC systems like CSF at Manchester. Users specify tasks to run in a workflow, with the main output being a workflow HDF5 file. The tool aims to make reproducibility and transparency easier, connect dispara
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Efficient Solver Techniques in CFD Simulations
This resource provides insights into the segregated solver approach in computational fluid dynamics (CFD) simulations, specifically focusing on the sweeping direction and its impact on computational efficiency and convergence rates. It discusses the benefits of employing the XY plane for 2D cases to
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Exploring Complexity in Computational Theory
Dive into a world of computational complexity and theory with a focus on topics such as NP, P, PH, PSPACE, NL, L, random vs. deterministic algorithms, and the interplay of time and space complexity. Discover insights on lower bounds, randomness, expanders, noise removal, and the intriguing question
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Exploring Computational Techniques with NLTK for Linguists
Dive into the world of computational techniques for linguists with NLTK in Lecture 24. Learn about list comprehensions, conditional forms, tokenization, part-of-speech tagging, parsing, chunking, concordance, similarity, common contexts, dispersion plots, and more. Discover where NLTK is installed o
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Understanding Computational Complexity Through Statistical Physics
In the age of vast data growth, tackling complex computational problems is crucial. Statistical physics can provide insights into handling the new challenges arising from the exponential increase in data. As we delve into understanding the complexity of computational tasks, it becomes evident that e
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Introduction to Priority Search Trees in Computational Geometry
This lecture outlines the structure and query process of Priority Search Trees (PST) in computational geometry. It covers heap-based point queries, range trees for windowing queries, handling query ranges in 1D and 2D spaces, and using heaps to efficiently handle query ranges. The content discusses
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Ladner's Theorem in Computational Complexity Theory
Ladner's Theorem is a significant result in computational complexity theory that deals with NP-intermediate problems, which are languages in NP neither in P nor NP-complete. The theorem states that if P is not equal to NP, then there must exist an NP-intermediate language. The proof involves a delic
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Understanding Computational Geometry: Triangulations and Art Gallery Guarding
Explore the concepts of triangulations and guarding art galleries in computational geometry. Learn about the problem of placing cameras or guards strategically in an art gallery to ensure every point is visible. Discover how polygons are defined, the variations in guarding strategies, and the use of
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Advancing Computational Modeling for National Security and Climate Missions
Irina Tezaur leads the Quantitative Modeling & Analysis Department, focusing on computational modeling and simulation of complex multi-scale, multi-physics problems. Her work benefits DOE nuclear weapons, national security, and climate missions. By employing innovative techniques like model order re
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Understanding Computational Biology: Proteins, DNA, RNA, Genetics, and Evolution
Computational Biology combines computational methods with molecular biology to solve biological problems. Explore topics like proteins, DNA, RNA, and genetics, learning about amino acids, nucleotides, and the genetic code. Understand the evolutionary processes of mutation and natural selection.
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Computational Geometry: Algorithms and Methods in Geometric Problem Solving
Explore the realm of computational geometry encompassing line segment crossing, convex hulls, Voronoi diagrams, and element distinctness reduction. Delve into techniques like line crossing checks, enumeration of cross points, and the sweep method, which are crucial for solving geometric problems eff
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The Early Introduction of Dynamic Programming in Computational Biology
The early integration of dynamic programming in computational biology, spearheaded by David Sankoff, revolutionized sequence comparison, multiple alignment, and phylogeny analyses. Sankoff's pioneering work in the 1970s laid the foundation for bioinformatics, recognizing the key role of algorithm de
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Understanding Algorithms, Pseudocode, and Flowcharts in Programming
Learn the fundamental concepts of algorithms, pseudocode, and flowcharts in programming through a series of detailed explanations and visual representations provided by Dr. Nouf Aljaffan. Explore the stages in program development, creating algorithms, computational thinking principles, and the pract
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Introduction to Computational Number Theory in Cryptography
Practical private-key cryptography can be done without advanced math, but understanding computational number theory is essential for public-key encryption. This field focuses on the computational difficulty of problems, analyzing algorithms' running times, classifying problems as easy or hard based
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Understanding Word Sense Disambiguation in Computational Lexical Semantics
Word Sense Disambiguation (WSD) is a crucial task in Computational Lexical Semantics, aiming to determine the correct sense of a word in context from a fixed inventory of potential word senses. This process involves various techniques such as supervised machine learning, unsupervised methods, thesau
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Understanding Word Sense Disambiguation in Computational Lexical Semantics
Explore the intricate world of word sense disambiguation in computational lexical semantics, covering supervised and unsupervised techniques, lexical sample and all-words tasks, and various approaches such as knowledge-based and machine learning. Delve into the complexities of interpreting different
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Understanding the Essence of Computer Science and Computational Thinking
Delve into the fundamentals of Computer Science and Computational Thinking through chapters discussing the nature of science, predictions in physics, and the distinction between Computer Science and Computer Information Systems. Explore the relationships between Math, Physics, and Computer Science i
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Advancing Auditory Enhancement: Integrating Spleeter with Advanced Remixing Techniques in The Cadenza Challenge 2023
Our project for The Cadenza Challenge 2023 focused on improving audio for headphone users with hearing loss by integrating Spleeter's deep learning capabilities. We utilized N-ALR prescriptions, Butterworth bandpass filters, and Dynamic Range Compression to enhance audio quality. By leveraging advan
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North American Computational Linguistics Olympiad: A Competition for High School Students
The North American Computational Linguistics Olympiad (NACLO) is a competition for high school students interested in linguistics, languages, and computation. It consists of an Open Round in January and an Invitational Round in March, with no prerequisites needed. Participants tackle easy problems i
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Mississippi Center for Supercomputing Research (MCSR) Overview
The Mississippi Center for Supercomputing Research (MCSR) supports computational research in various fields like Chemistry, Bioinformatics, Physics, Engineering, and Computer Science for Mississippi IHLs. They provide training to optimize computational resources, offer classes for computational trai
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Exploring Computational Theories of Brain Function
In this series of images and text snippets, the discussion revolves around the emerging field of computational theories of brain function. Various aspects such as symbolic memories, the relationship between the brain and computation, the emergence of the mind from the brain, and computational thinki
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Computational Earth Science Course Overview
Explore the world of Computational Earth Science with Bill Menke as the instructor and Emily Glazer as the teaching assistant. The course aims to help you become proficient in applying Python-based computational methods to understand dynamic Earth Science phenomena. Through modeling, you will gain i
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